P25: Large-Scale Adaptive Mesh Simulations Through Non-Volatile Byte-Addressable Memory
Authors: Bao Nguyen (Washington State University, Vancouver), Hua Tan (Washington State University, Vancouver), Xuechen Zhang (Washington State University, Vancouver)
Abstract: Octree-based mesh adaptation has enabled simulations of complex physical phenomena. Existing meshing algorithms were proposed with the assumption that computer memory is volatile. Consequently, for failure recovery, the in-core algorithms need to save memory states as snapshots with slow file I/Os. The out-of-core algorithms store octants on disks for persistence. However, neither of them was designed to leverage unique characteristics of non-volatile byte-addressable memory (NVBM). We propose a novel data structure Persistent Merged octree (PM-octree) for both meshing and in-memory storage of persistent octrees using NVBM. It is a multi-version data structure and can recover from failures using its earlier persistent version stored in NVBM. In addition, we design a feature-directed sampling approach to help dynamically transform the PM-octree layout for reducing NVBM-induced memory write latency.
Award: Best Poster Finalist (BP): no
Poster: pdf
Two-page extended abstract: pdf
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